| Description |
Overview
Have you ever been stuck with a file format that doesn't precisely conform to your needs, found yourself doing annoyingly repetitive data manipulations, or struggled to efficiently manage and explore your data? Python to the rescue!
Python is an open-source and general-purpose scripting language which runs on all major operating systems. It was designed to be easily read and written with comparatively simple syntax, and is thus a good choice for beginners in programming. Python is applied in many disciplines and is one of the most common languages for bioinformatics.
The Python community enthusiastically maintains a rich collection of libraries/modules for everything from web development to machine learning. Other programming languages such as R have comparable functionality to Python, however some tasks are more natural (and easier!) in Python.
In this course, participants will learn the basic concepts and data structures necessary to solve routine data manipulation tasks. Importantly, we will cover the concepts, terminology, and approach to documentation required to further develop skills in Python programming independently. The goal is to take control of your research questions in an independent manner.
Topics include:
- A basic introduction to Python scripting and computing in general
- Creating, populating, and modifying data structures
- Working with files : reading / writing
- Installing / Importing libraries/modules
- Writing functions
- Best practices in Python programming
- Debugging and documentation
Audience
This 3-day course is addressed to beginners who want to become familiar with writing Python code to accomplish common tasks such as automated data parsing, basic statistical operations and graphical representations.
For people who are proficient in programming: this course might be on the slow side for you and an intermediate python class is recommended (check regularly our upcoming training courses).
Learning objectives
By the end of this course, you will not only be prepared to learn more advanced bioinformatics-specific applications in forthcoming courses, but also be able to:
- Create, populate, and modify data structures
- Work with files: read and write files
- Install and import libraries and modules
- Write functions
- Apply best practices in Python programming
- Debug and document your own code |
| Information |
Prerequisites
Knowledge / competencies
This course is designed for beginners; there is no requirement for previous training in Python. However, we encourage completion of our "First Steps with UNIX" course or our "UNIX Fundamentals" tutorial. Basic concepts of algorithmics is a plus.
Technical
You are required to have your own laptop. We will be working with Python managed by Anaconda - a free and operating system (OS)-agnostic platform for organizing Python libraries and environments. It is bundled with Anaconda Navigator, a graphical user interface which will help ease you into what Python makes possible. We will discuss in detail what all of this precisely means during the course. In preparation, all you have to do is download and install Anaconda for your particular OS. Use any most recent version of Python (>= 3.7). If your disk space is limited, you can install Miniconda instead. However this lacks the Anaconda Navigator GUI and many of the packages distributed with Anaconda.
We will also be interacting with python via the jupyter notebook interface and we ask that you install jupyter notebook, via conda. |
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